Various techniques exist for analyzing electronic content and identifying key passages. Some of these techniques enable users explicitly to identify phrases or passages that they consider to be of importance. For example, eReaders may provide annotation tools that allow a user to highlight or otherwise mark text in an eBook or other electronic content that the user considers to be particularly interesting. There are also techniques that enable users to capture text and multimedia across different modalities. For example, a user may be able to capture text, images, or video from a web page, scanned document, or photograph.
Tools also exist for facilitating the identification of “quote” passages or passages that correspond to quotes that may be attributed to a particular speaker or other source (e.g., book, news publication, media outlet). Other tools track reader behavior by analyzing copy/paste events. These tools may track the portions of an electronic document (e.g., a web page) that a user copies and pastes, such as by highlighting with the cursor of a mouse or other input device and selecting the “copy” and “paste” functions associated with an application or device. Such information may be used by content creators for business intelligence. Moreover, certain implementations of monitoring users' copy/paste behavior may be used for providing attribution of copied/pasted material to its source (e.g., pasted text automatically includes a link or other information attributing it to the source from which it was copied).
Although the above techniques and solutions are useful in certain applications, each suffers from one or more drawbacks or disadvantages that hinder its suitability for use in other applications. For example, certain known methods of identifying key passages are limited to analyzing literal quotes. Moreover, some solutions are centered on providing analytics to content creators (e.g., publishers, writers) and provide little utility for content users or consumers. For example, methods for analyzing users' copy/paste behavior may provide attribution to a source or provide business intelligence to content creators, but fail to provide useful information to content users or consumers.